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Create a Count Plot with SeaBorn – Python Pandas
Count Plot in Seaborn is used to display the counts of observations in each categorical bin using bars. The seaborn.countplot() is used for this.
Let’s say the following is our dataset in the form of a CSV file − Cricketers.csv
At first, import the required 3 libraries −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt
Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv")
Example
Following is the code −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # Load data from a CSV file into a Pandas DataFrame dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") # plotting count plot with Age column sb.countplot(dataFrame["Age"]) # display plt.show()
Output
This will produce the following output −
Example
Let us see another example wherein we have used the hue parameter −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt # Load data from a CSV file into a Pandas DataFrame dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers.csv") # plotting count plot with Role column and hue as Academy sb.countplot( x= "Role", hue="Academy", data=dataFrame) # display plt.show()
Output
This will produce the following output −
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